The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
The stochastic approach for link-structure analysis (SALSA) and the TKC effect
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
Modern Information Retrieval
Focused Crawls, Tunneling, and Digital Libraries
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
Building implicit links from content for forum search
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
An empirical study on learning to rank of tweets
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Towards a quality-oriented real-time web crawler
WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
Retrieving similar discussion forum threads: a structure based approach
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
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Web forum is an important information resource. Each day innumerable postings on various topics are created in thousands of web forums in internet. However, only a small part of them are utilized for the reason that it is difficult to rank the postings importance. Unlike general web sites with hyperlinks in web pages created by editors, links in web forums are automatically generated, therefore, traditional link-based methods, such as famous PageRank are useless to rank postings. In this paper, we propose a novel algorithm named PostingRank to rank postings. The main idea of our method is to exploit the common repliers between postings and leverage the relationship between these common repliers. We build implicit links based on that co-repliers relation and construct a link graph. In the way of iterative calculation, each posting's importance score can be obtained. The experimental results demonstrate that our method can improve retrieval performance and outperforms traditional link-based methods.